CONFIGURATION OF AN IMPUTER MODEL
    2.
    发明申请

    公开(公告)号:WO2021213746A1

    公开(公告)日:2021-10-28

    申请号:PCT/EP2021/057211

    申请日:2021-03-22

    Abstract: Apparatus and methods of configuring an imputer model for imputing a second parameter. The method comprises inputting a first data set comprising values of a first parameter to the imputer model, and evaluating the imputer model to obtain a second data set comprising imputed values of the second parameter. The method further comprises obtaining a third data set comprising measured values of a third parameter, wherein the third parameter is correlated to the second parameter; obtaining a prediction model configured to infer values of the third parameter based on inputting values of the second parameter; inputting the second data set to the prediction model, and evaluating the prediction model to obtain inferred values of the third parameter; and configuring the imputer model based on a comparison of the inferred values and the measured values of the third parameter.

    CONFIGURATION OF AN IMPUTER MODEL
    4.
    发明公开

    公开(公告)号:EP3913435A1

    公开(公告)日:2021-11-24

    申请号:EP20175361.3

    申请日:2020-05-19

    Abstract: Apparatus and methods of configuring an imputer model for imputing a second parameter. The method comprises inputting a first data set comprising values of a first parameter to the imputer model, and evaluating the imputer model to obtain a second data set comprising imputed values of the second parameter. The method further comprises obtaining a third data set comprising measured values of a third parameter, wherein the third parameter is correlated to the second parameter; obtaining a prediction model configured to infer values of the third parameter based on inputting values of the second parameter; inputting the second data set to the prediction model, and evaluating the prediction model to obtain inferred values of the third parameter; and configuring the imputer model based on a comparison of the inferred values and the measured values of the third parameter.

    CONFIDENTIALITY-PRESERVING COLLABORATIVE MODEL FOR DERIVING INFORMATION ON A PRODUCTION SYSTEM

    公开(公告)号:EP4538938A1

    公开(公告)日:2025-04-16

    申请号:EP23202791.2

    申请日:2023-10-10

    Abstract: A method is presented for using a distributed network to derive information characterising a production system described by variables. The network comprises two probabilistic models implementing a graph comprising nodes associated with a corresponding one of the variables, and directed edges connecting respective pairs of the nodes. Each graph comprises an interface node for which the corresponding associated variable is common and normal nodes to which edge(s) are directed that are associated with a respective conditional probability table (CPT) specifying a probability of the variable being in a set of states based on the variables associated with the corresponding one or more nodes from which the one or more edges are directed. The interface node is associated with a partial CPT of the common variable. The method comprises generating, using the at least two models, conditioned data specifying a probability distribution of the state of the common variable.

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